计算机科学
边缘计算
云计算
农业生产力
可靠性(半导体)
GSM演进的增强数据速率
农业
计算机安全
计算机网络
分布式计算
电信
操作系统
生物
物理
量子力学
功率(物理)
生态学
作者
Qing Zhou,Minghua Xiao,Lei Lu,Jun Zeng,Wenting He,Chao Li,Yulun Shi
摘要
Collecting environmental information of crop growth and dynamically adjusting agricultural production has been proved an effective way to improve the total agricultural yield. Agricultural IoT technology, which integrates the information sensing equipment, communication network, and information processing systems, can support such an intelligent manner in the agricultural environment. Traditional agricultural IoT could meet the service demand of small-scale agricultural production scenarios to a certain extent. However, the emerging application scenario of the agricultural environment is becoming more and more complicated, and the data nodes of the underlying access to IoT backend system are increasing in large number, while the upper-layer applications are requiring high quality of data service. Hence, the traditional architecture-based (i.e., centralised cloud computing) IoT systems suffer from the problems such as small network coverage, data security issue, and limited power supply time while attempting to provide high-quality services at the edge of the network. Emerging edge computing offers the opportunity to solve these issues. This paper builds an intelligent IoT system for agricultural environment monitoring by integrating edge computing and artificial intelligence. We conducted an experiment to validate the proposed system considering the reliability and usability. The experimental results prove the system’s reliability (e.g., data packet loss rate is less than 0.1%). The proposed system achieves the concurrency of 500TPS and the average response time of 300 ms, which meet the practical requirements in agricultural environment monitoring.
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